Main MRPT website > C++ reference for MRPT 1.4.0
CPosePDFSOG.h
Go to the documentation of this file.
1/* +---------------------------------------------------------------------------+
2 | Mobile Robot Programming Toolkit (MRPT) |
3 | http://www.mrpt.org/ |
4 | |
5 | Copyright (c) 2005-2016, Individual contributors, see AUTHORS file |
6 | See: http://www.mrpt.org/Authors - All rights reserved. |
7 | Released under BSD License. See details in http://www.mrpt.org/License |
8 +---------------------------------------------------------------------------+ */
9#ifndef CPosePDFSOG_H
10#define CPosePDFSOG_H
11
12#include <mrpt/poses/CPosePDF.h>
15
16
17namespace mrpt
18{
19 namespace poses
20 {
21 // This must be added to any CSerializable derived class:
23
24 /** Declares a class that represents a Probability Density function (PDF) of a 2D pose \f$ p(\mathbf{x}) = [x ~ y ~ \phi ]^t \f$.
25 * This class implements that PDF as the following multi-modal Gaussian distribution:
26 *
27 * \f$ p(\mathbf{x}) = \sum\limits_{i=1}^N \omega^i \mathcal{N}( \mathbf{x} ; \bar{\mathbf{x}}^i, \mathbf{\Sigma}^i ) \f$
28 *
29 * Where the number of modes N is the size of CPosePDFSOG::m_modes
30 *
31 * See mrpt::poses::CPosePDF for more details.
32 *
33 * \sa CPose2D, CPosePDF, CPosePDFParticles
34 * \ingroup poses_pdf_grp
35 */
37 {
38 // This must be added to any CSerializable derived class:
40
41 public:
42 /** The struct for each mode:
43 */
45 {
47 mean(),
48 cov(),
49 log_w(0)
50 { }
51
54
55 /** The log-weight
56 */
57 double log_w;
58
59 public:
61 };
62
64 typedef CListGaussianModes::const_iterator const_iterator;
65 typedef CListGaussianModes::iterator iterator;
66
67 protected:
68 void assureSymmetry(); //!< Ensures the symmetry of the covariance matrix (eventually certain operations in the math-coprocessor lead to non-symmetric matrixes!)
69
70 CListGaussianModes m_modes; //!< The list of SOG modes
71
72 public:
73 /** Default constructor
74 * \param nModes The initial size of CPosePDFSOG::m_modes */
75 CPosePDFSOG( size_t nModes = 1 );
76
77 size_t size() const { return m_modes.size(); } //!< Return the number of Gaussian modes.
78 bool empty() const { return m_modes.empty(); } //!< Return whether there is any Gaussian mode.
79
80
81 void clear(); //!< Clear the list of modes
82
83 /** Access to individual beacons */
84 const TGaussianMode& operator [](size_t i) const {
85 ASSERT_(i<m_modes.size())
86 return m_modes[i];
87 }
88 /** Access to individual beacons */
89 TGaussianMode& operator [](size_t i) {
90 ASSERT_(i<m_modes.size())
91 return m_modes[i];
92 }
93
94 /** Access to individual beacons */
95 const TGaussianMode& get(size_t i) const {
96 ASSERT_(i<m_modes.size())
97 return m_modes[i];
98 }
99 /** Access to individual beacons */
100 TGaussianMode& get(size_t i) {
101 ASSERT_(i<m_modes.size())
102 return m_modes[i];
103 }
104
105 /** Inserts a copy of the given mode into the SOG */
106 void push_back(const TGaussianMode& m) {
107 m_modes.push_back(m);
108 }
109
110 iterator begin() { return m_modes.begin(); }
111 iterator end() { return m_modes.end(); }
112 const_iterator begin() const { return m_modes.begin(); }
113 const_iterator end()const { return m_modes.end(); }
114
115 iterator erase(iterator i) { return m_modes.erase(i); }
116
117 void resize(const size_t N); //!< Resize the number of SOG modes
118
119 /** Merge very close modes so the overall number of modes is reduced while preserving the total distribution.
120 * This method uses the approach described in the paper:
121 * - "Kullback-Leibler Approach to Gaussian Mixture Reduction" AR Runnalls. IEEE Transactions on Aerospace and Electronic Systems, 2007.
122 *
123 * \param max_KLd The maximum KL-divergence to consider the merge of two nodes (and then stops the process).
124 */
125 void mergeModes( double max_KLd = 0.5, bool verbose = false );
126
127 void getMean(CPose2D &mean_pose) const MRPT_OVERRIDE; //!< Returns an estimate of the pose, (the mean, or mathematical expectation of the PDF) \sa getCovariance
128 void getCovarianceAndMean(mrpt::math::CMatrixDouble33 &cov,CPose2D &mean_point) const MRPT_OVERRIDE; //!< Returns an estimate of the pose covariance matrix (3x3 cov matrix) and the mean, both at once. \sa getMean
129 void getMostLikelyCovarianceAndMean(mrpt::math::CMatrixDouble33 &cov,CPose2D &mean_point) const; //!< For the most likely Gaussian mode in the SOG, returns the pose covariance matrix (3x3 cov matrix) and the mean. \sa getMean
130 void normalizeWeights(); //!< Normalize the weights in m_modes such as the maximum log-weight is 0
131
132 void copyFrom(const CPosePDF &o) MRPT_OVERRIDE; //!< Copy operator, translating if necesary (for example, between particles and gaussian representations)
133
134 /** Save the density to a text file, with the following format:
135 * There is one row per Gaussian "mode", and each row contains 10 elements:
136 * - w (The weight)
137 * - x_mean (gaussian mean value)
138 * - y_mean (gaussian mean value)
139 * - phi_mean (gaussian mean value)
140 * - C11 (Covariance elements)
141 * - C22 (Covariance elements)
142 * - C33 (Covariance elements)
143 * - C12 (Covariance elements)
144 * - C13 (Covariance elements)
145 * - C23 (Covariance elements)
146 */
147 void saveToTextFile(const std::string &file) const MRPT_OVERRIDE;
148
149 /** this = p (+) this. This can be used to convert a PDF from local coordinates to global, providing the point (newReferenceBase) from which
150 * "to project" the current pdf. Result PDF substituted the currently stored one in the object. */
151 void changeCoordinatesReference(const CPose3D &newReferenceBase ) MRPT_OVERRIDE;
152
153 void rotateAllCovariances(const double &ang); //!< Rotate all the covariance matrixes by replacing them by \f$ \mathbf{R}~\mathbf{COV}~\mathbf{R}^t \f$, where \f$ \mathbf{R} = \left[ \begin{array}{ccc} \cos\alpha & -\sin\alpha & 0 \\ \sin\alpha & \cos\alpha & 0 \\ 0 & 0 & 1 \end{array}\right] \f$
154 void drawSingleSample( CPose2D &outPart ) const MRPT_OVERRIDE; //!< Draws a single sample from the distribution
155 void drawManySamples( size_t N, std::vector<mrpt::math::CVectorDouble> & outSamples ) const MRPT_OVERRIDE; //!< Draws a number of samples from the distribution, and saves as a list of 1x3 vectors, where each row contains a (x,y,phi) datum.
156 void inverse(CPosePDF &o) const MRPT_OVERRIDE; //!< Returns a new PDF such as: NEW_PDF = (0,0,0) - THIS_PDF
157
158 void operator += ( const mrpt::poses::CPose2D &Ap); //!< Makes: thisPDF = thisPDF + Ap, where "+" is pose composition (both the mean, and the covariance matrix are updated).
159
160 double evaluatePDF( const mrpt::poses::CPose2D &x, bool sumOverAllPhis = false ) const; //!< Evaluates the PDF at a given point.
161 double evaluateNormalizedPDF( const mrpt::poses::CPose2D &x ) const; //!< Evaluates the ratio PDF(x) / max_PDF(x*), that is, the normalized PDF in the range [0,1].
162
163 /** Evaluates the PDF within a rectangular grid (and a fixed orientation) and saves the result in a matrix (each row contains values for a fixed y-coordinate value). */
165 const double & x_min,
166 const double & x_max,
167 const double & y_min,
168 const double & y_max,
169 const double & resolutionXY,
170 const double & phi,
171 mrpt::math::CMatrixD &outMatrix,
172 bool sumOverAllPhis = false );
173
174 /** Bayesian fusion of two pose distributions, then save the result in this object (WARNING: Currently p1 must be a mrpt::poses::CPosePDFSOG object and p2 a mrpt::poses::CPosePDFGaussian object) */
175 void bayesianFusion(const CPosePDF &p1,const CPosePDF &p2, const double &minMahalanobisDistToDrop=0 ) MRPT_OVERRIDE;
176
177 }; // End of class def.
179 } // End of namespace
180} // End of namespace
181#endif
#define DEFINE_SERIALIZABLE(class_name)
This declaration must be inserted in all CSerializable classes definition, within the class declarati...
#define DEFINE_SERIALIZABLE_POST_CUSTOM_BASE(class_name, base_name)
#define DEFINE_SERIALIZABLE_PRE_CUSTOM_BASE(class_name, base_name)
This declaration must be inserted in all CSerializable classes definition, before the class declarati...
This class is a "CSerializable" wrapper for "CMatrixTemplateNumeric<double>".
Definition: CMatrixD.h:31
A numeric matrix of compile-time fixed size.
A class used to store a 2D pose.
Definition: CPose2D.h:37
A class used to store a 3D pose (a 3D translation + a rotation in 3D).
Definition: CPose3D.h:73
Declares a class that represents a probability density function (pdf) of a 2D pose (x,...
Definition: CPosePDF.h:40
Declares a class that represents a Probability Density function (PDF) of a 2D pose .
Definition: CPosePDFSOG.h:37
void rotateAllCovariances(const double &ang)
Rotate all the covariance matrixes by replacing them by , where .
void resize(const size_t N)
Resize the number of SOG modes.
double evaluateNormalizedPDF(const mrpt::poses::CPose2D &x) const
Evaluates the ratio PDF(x) / max_PDF(x*), that is, the normalized PDF in the range [0,...
const_iterator begin() const
Definition: CPosePDFSOG.h:112
const TGaussianMode & get(size_t i) const
Access to individual beacons.
Definition: CPosePDFSOG.h:95
iterator erase(iterator i)
Definition: CPosePDFSOG.h:115
mrpt::aligned_containers< TGaussianMode >::vector_t CListGaussianModes
Definition: CPosePDFSOG.h:63
void normalizeWeights()
Normalize the weights in m_modes such as the maximum log-weight is 0.
void drawSingleSample(CPose2D &outPart) const MRPT_OVERRIDE
Draws a single sample from the distribution.
void copyFrom(const CPosePDF &o) MRPT_OVERRIDE
Copy operator, translating if necesary (for example, between particles and gaussian representations)
void getCovarianceAndMean(mrpt::math::CMatrixDouble33 &cov, CPose2D &mean_point) const MRPT_OVERRIDE
Returns an estimate of the pose covariance matrix (3x3 cov matrix) and the mean, both at once.
void mergeModes(double max_KLd=0.5, bool verbose=false)
Merge very close modes so the overall number of modes is reduced while preserving the total distribut...
void evaluatePDFInArea(const double &x_min, const double &x_max, const double &y_min, const double &y_max, const double &resolutionXY, const double &phi, mrpt::math::CMatrixD &outMatrix, bool sumOverAllPhis=false)
Evaluates the PDF within a rectangular grid (and a fixed orientation) and saves the result in a matri...
CListGaussianModes::iterator iterator
Definition: CPosePDFSOG.h:65
bool empty() const
Return whether there is any Gaussian mode.
Definition: CPosePDFSOG.h:78
const_iterator end() const
Definition: CPosePDFSOG.h:113
void clear()
Clear the list of modes.
void saveToTextFile(const std::string &file) const MRPT_OVERRIDE
Save the density to a text file, with the following format: There is one row per Gaussian "mode",...
void getMostLikelyCovarianceAndMean(mrpt::math::CMatrixDouble33 &cov, CPose2D &mean_point) const
For the most likely Gaussian mode in the SOG, returns the pose covariance matrix (3x3 cov matrix) and...
CListGaussianModes::const_iterator const_iterator
Definition: CPosePDFSOG.h:64
void bayesianFusion(const CPosePDF &p1, const CPosePDF &p2, const double &minMahalanobisDistToDrop=0) MRPT_OVERRIDE
Bayesian fusion of two pose distributions, then save the result in this object (WARNING: Currently p1...
size_t size() const
Return the number of Gaussian modes.
Definition: CPosePDFSOG.h:77
void assureSymmetry()
Ensures the symmetry of the covariance matrix (eventually certain operations in the math-coprocessor ...
double evaluatePDF(const mrpt::poses::CPose2D &x, bool sumOverAllPhis=false) const
Evaluates the PDF at a given point.
void push_back(const TGaussianMode &m)
Inserts a copy of the given mode into the SOG.
Definition: CPosePDFSOG.h:106
void drawManySamples(size_t N, std::vector< mrpt::math::CVectorDouble > &outSamples) const MRPT_OVERRIDE
Draws a number of samples from the distribution, and saves as a list of 1x3 vectors,...
void changeCoordinatesReference(const CPose3D &newReferenceBase) MRPT_OVERRIDE
this = p (+) this.
void getMean(CPose2D &mean_pose) const MRPT_OVERRIDE
Returns an estimate of the pose, (the mean, or mathematical expectation of the PDF)
CListGaussianModes m_modes
The list of SOG modes.
Definition: CPosePDFSOG.h:70
CPosePDFSOG(size_t nModes=1)
Default constructor.
void inverse(CPosePDF &o) const MRPT_OVERRIDE
Returns a new PDF such as: NEW_PDF = (0,0,0) - THIS_PDF.
TGaussianMode & get(size_t i)
Access to individual beacons.
Definition: CPosePDFSOG.h:100
EIGEN_STRONG_INLINE double mean() const
Computes the mean of the entire matrix.
#define MRPT_MAKE_ALIGNED_OPERATOR_NEW
Definition: memory.h:112
#define ASSERT_(f)
Definition: mrpt_macros.h:261
#define MRPT_OVERRIDE
C++11 "override" for virtuals:
Definition: mrpt_macros.h:28
This is the global namespace for all Mobile Robot Programming Toolkit (MRPT) libraries.
std::vector< TYPE1, Eigen::aligned_allocator< TYPE1 > > vector_t
The struct for each mode:
Definition: CPosePDFSOG.h:45
mrpt::math::CMatrixDouble33 cov
Definition: CPosePDFSOG.h:53



Page generated by Doxygen 1.9.5 for MRPT 1.4.0 SVN: at Sun Nov 27 02:56:59 UTC 2022